Low dose digital tomosynthesis system and method using artificial intelligence

ABSTRACT

A mobile radiography apparatus is configured to sparsely sample radiographic projection images to generate high resolution tomosynthesis volume images using a digital radiographic detector that is mechanically uncoupled from the x-ray source and an artificial intelligence network. The artificial intelligence network is trained to correct a volume image generated from sparsely sample projection images to generate the high resolution tomosynthesis volume images.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent application claims the benefit of U.S. Provisional Application U.S. Ser. No. 62/963,586, filed on Jan. 21, 2020, entitled LOW DOSE DIGITAL TOMOSYNTHESIS SYSTEM AND METHOD BASED ON ARTIFICIAL INTELLIGENCE, in the name of Wang et al., and is a continuation-in-part patent application of U.S. patent application Ser. No. 17/115,869, filed on Dec. 9, 2020, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the name of Sehnert, et al., which is a continuation-in-part patent application of U.S. patent application Ser. No. 17/082,080, filed on Oct. 28, 2020, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the name of Sehnert, et al., which is a continuation patent application of U.S. patent application Ser. No. 16/692,362, filed on Nov. 22, 2019, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the name of Lin, et al., which is a continuation patent application of U.S. patent application Ser. No. 15/971,213, filed on May 4, 2018, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the name of Lin, et al., which claims the benefit of U.S. Provisional Application U.S. Ser. No. 62/507,288, provisionally filed on May 17, 2017, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the name of Lin et al., and U.S. Provisional Application U.S. Ser. No. 62/598,519, provisionally filed on Dec. 14, 2017, entitled SELF-CALIBRATING TECHNIQUE FOR X-RAY IMAGING SCANNERS, in the names of Lin et al., which are both hereby incorporated herein by reference in their entirety.

TECHNICAL FIELD

This disclosure relates generally to the field of medical imaging, and in particular to a mobile radiography imaging apparatus. More particularly, this disclosure relates to a mobile x-ray imaging system having a tomosynthesis and artificial intelligence capability.

BACKGROUND

Portable radiography is a common modality employed for imaging patients in the ICU to evaluate patient health and determine best treatment. However, abnormal findings on portable chest X-ray images of ICU patients are frequently nonspecific. Nonspecific findings are typically visualized as regions of opacity in the lung, but without any clear indication of whether the pathology is in the airways (lung collapse), airspaces (consolidation) or within the pleura (effusions). Establishing the correct diagnosis is critical to initiate appropriate patient management. Differentiating among types of pleural effusions is another common task assisted by imaging in the ICU and can be challenging and critical to patient care. Various types of fluids can cause plural effusions, e.g., blood (hemothorax), pus (pyothorax or empyema), and water/serous fluid (hydrothorax). Furthermore, each cause requires a different course of action. Therefore, improved ability to identify the cause is required. Knowing the cause with greater probability would be expected to enhance patient care. In cases where portable radiography is found insufficient, CT is often prescribed as it provides a fully 3D image, however, this can be disruptive to the patient who is in critical care. Obtaining a CT in such situations requires transporting an unstable patient out of the ICU which increases risk to the patient's already critical condition. An alternative to CT could be a bedside x-ray imaging system that is capable of providing a form of 3D imagery such as digital tomosynthesis that will improve the specificity of findings as compared with standard portable chest radiography. Such a system would be beneficial because it would reduce the need to transport unstable ICU patients for CT exams.

Digital x-ray tomosynthesis is an imaging technique that enables three-dimensional imaging of a patient using a large-area flat panel digital radiographic detector typically used for conventional (single projection) radiography. A finite number of projection images over a limited angular range, typically between 20° and 40°, are acquired by varying the relative orientations of the x-ray tube, or x-ray source, patient and detector, typically a digital radiographic (DR) detector. This is usually accomplished by either moving both the detector and x-ray source or by fixing the position of the detector, or source, and moving the x-ray source, or detector, respectively. Three-dimensional data is reconstructed from the captured projections and may be displayed in the form of any number of slices through the patient anatomy, each parallel to the detector plane. A consequence of limited angular scanning is that the in-depth resolution is lower than the in-plane resolution of the reconstructed object.

Reconstruction of volumetric data, or 3D x-ray images, from a tomosynthesis system requires knowledge of the underlying capture geometry, including the orientation and spatial position of the detector relative to the x-ray source, the movement and position of the source relative to the detector, and potential patient motion. Precise geometric information of the imaging system (orientation of the X-ray detector, and relative locations of the X-ray tube head with respect to the X-ray detector during 2D projection image acquisition) affect the image quality of the reconstructed volume images. Mismapping between object space and the acquired 2D projection images can degrade spatial resolution and lead to image defects, such as ring artifacts.

In a conventional tomosynthesis system, many of the geometric variables are known, as the detector position is precisely specified and the relationship between source and detector is also well established. For stationary imaging scanners, acquisition geometry is fixed by the mechanical coupling of source and detector, such in a C-arm configuration or other type of gantry arrangement. Calibration of this geometry is straightforward, using a calibration phantom prior to image acquisition.

For a bed-side tomosynthesis system using a mobile radiography apparatus, however, the detector is mechanically uncoupled from the x-ray source. Thus, the capture geometry is not fixed by system mechanics and can be difficult to determine with the desired accuracy. Mobile x-ray imaging scanners used for tomosynthesis are designed for seriously ill patients who cannot be transported to, walk to, or stand in front of, stationary imaging scanners having fixed geometry. Instead, in order to image these patients, the detector is often manually positioned under the bed-ridden patient. In this acquisition environment, without the benefit of mechanically fixed source-to-detector geometry, other approaches are needed in order to accurately determine the geometry information in real time.

The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.

SUMMARY

A mobile radiography apparatus is configured to sparsely sample radiographic projection images to generate high resolution tomosynthesis volume images using a digital radiographic detector that is mechanically uncoupled from the x-ray source, and an artificial intelligence network. An artificial intelligence module is trained to generate a high resolution volume image from sparsely sampled projection image. An advantage that may be realized in the practice of some disclosed embodiments of the present invention is a reduced radiation dose to the patient.

In one embodiment, a computer implemented radiographic image processing method comprises training a convolutional neural network to correct image defects in an image volume reconstructed from sparsely captured tomosynthesis projection images. Sparsely captured tomosynthesis projection images of a patient anatomy are obtained using a mobile radiography apparatus and a portable DR detector mechanically uncoupled from the mobile radiography apparatus. A sparse volume image of the patient anatomy is reconstructed using the sparsely captured tomosynthesis projection images and a trained convolutional neural network corrects the sparse volume image and outputs a corrected high resolution sparse volume image.

In one embodiment, a mobile radiography imaging system comprises a mobile base, a support arm attached to the mobile base, an x-ray tube head attached to one end of the support arm, and a portable DR detector mechanically uncoupled from the x-ray tube head. The system is configured to sparsely capture tomosynthesis projection images of a patient anatomy over an angular range. A processing portion of the system reconstructs a sparse volume image of the patient anatomy using the sparsely captured tomosynthesis projection images. An artificial intelligence module trained to correct the reconstructed sparse volume image outputs a corrected high resolution volume image.

This disclosure describes a method and system that is uniquely designed for high speed digital tomosynthesis acquisition of a patient body part at low dose. Further, the system provides a method for synthesizing from the series of tomosynthesis projections that are acquired over an angular range prior to or after 3D (volume) reconstruction, a standard general radiographic projection image slice of a patient body part from any specified view angle encompassed within said angular range.

The components of the system include a portable digital x-ray machine that is equipped with a portable digital radiography (DR) detector having high detective quantum efficiency and rapid readout speed capability, either an array of stationary x-ray sources that are collimated such that the array of x-ray sources can be used to expose an area of the body from varying angular positions in rapid sequence, or the exposures are achieved by rapidly moving a single x-ray source through varying angular positions, and deep learning-based algorithms that are used to reconstruct a high quality tomosynthesis volume image from a sparsely sampled series of projection images, or projection images captured over a limited angular range, or projection images captured over a wider angular separation, or projection images captured at reduced dose (energy level) when compared to a dose level in a nominally captured digital radiographic tomosynthesis exam.

Such a system would enable tomosynthesis images to be captured at a critically ill patient's bedside as a new standard of care supplanting standard portable digital radiography, because both tomosynthesis (3D) and general projection images could be acquired at patient dose levels that are comparable to current portable digital radiography systems currently in use. Conventional tomosynthesis utilizes an angular sampling rate that is less than or equal to one degree per projection. For example, a standard chest exam will use a total of sixty projections across a +/−15 degree angle, the angular sampling rate is about 0.5 degree per projection. In this disclosure, one sparse sampling technique uses a wide angular separation in between tomosynthesis projection image captures ranging from about two to about five degrees, which will greatly reduce the number tomosynthesis projections that need to be captured. This would greatly reduce the total acquisition time and patient motion artifacts. Additionally, the exposure technique settings in a conventional tomosynthesis system exposes the patient to about five to twenty times of the radiation exposure with a standard radiography for diagnostics. In this disclosure, as the number of projections are significantly reduced, the total exposure level associated with tomosynthesis will range from one to two times that of a standard radiography.

Achieving tomosynthesis dose levels similar to general radiography can be achieved through employing deep learning methods for image reconstruction or as a post-processing step following conventional reconstruction methods. Through deep learning techniques, the number of projection images can be significantly reduced while simultaneously decreasing the radiation dose per projection. Normally, using ordinary means for tomosynthesis reconstruction, a significant reduction in the number of projections introduces confounding streaking artifacts, while reducing the radiation dose leads to significant levels of noise. However, deep learning methods have been shown to overcome these limitations to image quality.

Digitally reconstructed radiography (DRR) can be synthesized from the reconstructed tomosynthesis volume after streaking artifact removal and noise reduction. Forward projection is one of the methods can generate DRR, however, this method would not be able to leverage the original projection images to further improve the DRR spatial resolution. As disclosed herein, the noise level in each tomosynthesis projection image is reduced using AI methods, then AI will use both the reconstructed tomosynthesis volume and optionally at least one of the projection images that is nearest to the DRR projection angle to create an improved image.

The summary descriptions above are not meant to describe individual separate embodiments whose elements are not interchangeable. In fact, many of the elements described as related to a particular embodiment can be used together with, and possibly interchanged with, elements of other described embodiments. Many changes and modifications may be made within the scope of the present invention without departing from the spirit thereof, and the invention includes all such modifications.

This brief description of the invention is intended only to provide a brief overview of subject matter disclosed herein according to one or more illustrative embodiments, and does not serve as a guide to interpreting the claims or to define or limit the scope of the invention, which is defined only by the appended claims. This brief description is provided to introduce an illustrative selection of concepts in a simplified form that are further described below in the detailed description. This brief description is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all disadvantages noted in the background.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the features of the invention can be understood, a detailed description of the invention may be had by reference to certain embodiments, some of which are illustrated in the accompanying drawings. It is to be noted, however, that the drawings illustrate only certain embodiments of this invention and are therefore not to be considered limiting of its scope, for the scope of the invention encompasses other equally effective embodiments. The drawings below are intended to be drawn neither to any precise scale with respect to relative size, angular relationship, relative position, or timing relationship, nor to any combinational relationship with respect to interchangeability, substitution, or representation of a required implementation, emphasis generally being placed upon illustrating the features of certain embodiments of the invention. In the drawings, like numerals are used to indicate like parts throughout the various views. Thus, for further understanding of the invention, reference can be made to the following detailed description, read in connection with the drawings in which:

FIG. 1 is a diagram that shows a perspective view of one embodiment of a mobile radiography unit for use as a portable imaging system for tomosynthesis or other volume imaging.

FIG. 2 is a perspective view that shows an embodiment of a mobile radiography apparatus in position for volume imaging.

FIG. 3A is a perspective view that shows one embodiment of aspects of the image capture metrics and behavior that relate to geometric calibration for a mobile radiology apparatus when used for tomosynthesis and other volume imaging.

FIG. 3B is a perspective view that shows additional aspects of the image capture metrics and x-ray head translation related to geometric calibration for a mobile radiology apparatus when used for tomosynthesis and other volume imaging.

FIG. 4 is a schematic cross-section of one embodiment of a portion of a conventional x-ray tube head.

FIG. 5 is a perspective view showing the function of one embodiment of a collimator light, which projects a pattern of light to assist registration of the patient to the source.

FIG. 6 is a schematic diagram showing one embodiment of components of a self-calibrating apparatus for a mobile radiography apparatus.

FIG. 7 is a logic flow diagram that shows one embodiment of a sequence for calibration of a mobile radiography apparatus having a detector that is not mechanically coupled to the x-ray source.

FIGS. 8A-8E illustrate arrangements of cold cathode or carbon nanotube x-ray sources configured to be secured to a tube head.

FIG. 9 illustrates different configurations of radiopaque markers.

FIG. 10 is a schematic diagram showing a one embodiment of a multiple source tube head and multiple radiopaque marker surfaces positioned in x-ray beams.

FIG. 11 is a schematic diagram of one embodiment of a tube head and marker positioning.

FIG. 12 is a schematic diagram of another embodiment of a tube head and marker positioning.

FIG. 13 is a schematic diagram of another embodiment of a tube head and marker positioning.

FIG. 14 illustrates patient positioning and one embodiment of a multiple source tube head.

FIG. 15 illustrates patient positioning and one embodiment of a multiple source tube head and alternative mounts for radiopaque markers.

FIG. 16 is a schematic of one embodiment of a marker support holder.

FIGS. 17A-17B illustrate sparse capture techniques for tomosynthesis projection images.

FIG. 18 illustrates an exemplary method of determining an angular range.

FIG. 19 illustrates one exemplary training method for an artificial intelligence network or module.

FIG. 20 illustrates one exemplary use of a trained artificial intelligence network or module.

FIG. 21 is a flow chart of an exemplary method of generating high resolution tomosynthesis volume images based on sparsely sampled radiographic projection images.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The following is a description of exemplary embodiments of the invention, reference being made to the drawings in which the same reference numerals identify the same elements of structure in each of the several figures. Where they are used, the terms “first”, “second”, and so on, do not necessarily denote any ordinal or priority relation, but may be used for more clearly distinguishing one element or time interval from another.

Portable radiographic systems are routinely used in hospitals. Compared to standard projection radiography, volume imaging apparatus such as tomosynthesis apparatus provide improved depiction of fine details not visible in normal radiographs due to overlying structures. These benefits provide an impetus to develop portable volume imaging systems that can be utilized in the intensive care unit, emergency department, and operating rooms, where moving the patient is either impracticable or ill-advised due to the risk of harm to the patient.

The image quality of the reconstruction depends upon accurate knowledge of the acquisition scan geometry, including spatial and angular positions of the x-ray source and detector for each projection. Uncertainties in the scan geometry can lead to artifacts and/or blurring in the reconstructed object. The development of portable volume imaging systems has been hampered by difficulties in accurately determining the acquisition scan geometry. There remains a need for improved X-ray volume imaging systems that can be made, or are, portable and still provide reliable clinical images and data at a much reduced radiation dose to patients.

FIG. 1 is a diagram that shows a perspective view of a mobile radiography unit 100 that can be used together with portable radiographic detectors or flat panel detectors that are mechanically uncoupled from the radiation source, and the mobile radiography apparatus 100, according to embodiments of the application disclosed herein. The exemplary mobile x-ray or radiographic apparatus 100 of FIG. 1 can be employed for digital radiographic (DR) imaging and/or tomosynthesis or tomographic imaging. As shown in FIG. 1, a mobile radiography apparatus 100 can include a moveable transport frame 120 that includes a first display 110 and an optional second display 110′ to display relevant information such as obtained images and related data, as well as operator inputs to control firing an x-ray source in x-ray tube head 140. As shown in FIG. 1, the second display 110′ can be pivotably mounted at the x-ray source, x-ray tube, or x-ray head 140 to be viewable/touchable from a 360 degree area.

The displays 110, 110′ can provide an input screen for an operator to implement or control (e.g., touch screens) functions such as generating, storing, transmitting, modifying, and printing of the obtained, or captured x-ray image(s), and can include an integral (e.g., touch screen) or separate control panel (not shown) to assist in implementing functions such as generating, storing, transmitting, modifying, and printing of obtained, or captured, x-ray images. An optional touchpad 150 allows support functions such as operator identification.

For mobility, the mobile radiographic apparatus 100 can have one or more wheels 115 and one or more handle grips 125, typically provided at waist-level, arm-level, or hand-level, that help an operator to move and to guide the mobile radiographic apparatus 100 to its intended location. A self-contained battery pack (e.g., rechargeable) can provide source power, which can reduce or eliminate the need for operation near a power outlet. Further, the self-contained battery pack can be configured to provide power for motorized wheels to transport the entire mobile radiography unit 100 to its intended location.

For storage, the mobile radiographic apparatus 100 can include an area/holder 134 (FIG. 2) for holding/storing one or more digital radiographic (DR) detectors 20 or computed radiography cassettes. The area/holder 134 can be a storage area disposed on the frame 120 configured to removably retain at least one digital radiography (DR) detector 20. The storage area 134 can be configured to hold a plurality of detectors 20 and can also be configured to hold one size or multiple sizes of DR detectors.

Still referring to FIG. 1, a control logic processor 130 provides the control logic for image processing and identification of the position of the detector 20 relative to the x-ray source in the tube head 140. Image processing can be provided by the control logic processor 130 that is part of mobile radiography apparatus 100 itself, or can be provided by one or more external computers, such as a control console, and other processors networked in signal communication with mobile radiography apparatus 100.

Mounted to frame 120 is a support member or column 135 that supports x-ray head 140, also called an x-ray tube, tube head, or generator, that includes the x-ray source and that can be mounted to the support member or column 135. In the embodiment shown in FIG. 1, the support member or column 135 can include a second horizontal telescoping section 30 that extends outward at a fixed or variable distance from the vertical first section where the second section is configured to ride vertically up and down the first section to the desired height for obtaining the radiographic image of a patient. In addition, the support member or column 135 vertical section is rotatably attached to the moveable frame 120 to allow manual rotation of the support member or column 135 around a vertical axis. In another embodiment, the tube head 140 can be rotatably coupled to the support column 135. In another exemplary embodiment, an articulated member of the support column that bends at a joint mechanism can allow movement of the x-ray tube head 140 over a range of vertical and horizontal positions. Height settings for the x-ray tube head 140 can range from low height for imaging feet and lower extremities to shoulder height and above for imaging the upper body portions of patients in various positions.

The perspective views of FIG. 2 shows mobile radiography apparatus 100 in position for tomosynthesis or tomographic imaging. Telescoping horizontal section 30 of the support member or column 135 is extendible and retractable in a linear direction 201 away from and toward the vertical section of support member or column 135. A patient 14 is lying flat on a bed or stretcher with a DR detector 20 fitted behind the patient 14, with respect to the x-ray source in the tube head 140. There is no inherent mechanical linkage or alignment between x-ray tube head 140 and the detector 20, and so conventional calibration of source/detector geometry prior to exposure is not feasible. The x-ray source in the tube head 140 is moved to several imaging positions, or angles, relative to the portable DR detector 20 by extending and/or retracting the horizontal section 30. A tomosynthesis projection image of the patient 14 is captured in the portable DR detector at each imaging position.

The perspective views of FIGS. 3A and 3B show aspects of the image capture metrics and behavior that relate to geometric calibration for mobile radiology apparatus 100 when used for tomosynthesis or other volume imaging. A source-to-image distance SID can be approximated based on known factors, such as bed height and column height for the mobile radiography apparatus 100. Even where the SID can be accurately identified, however, there are additional calibration metrics that must be known. These include factors such as skew of the detector 20 relative to the x-ray source in the tube head 140, as shown in FIG. 3A, and the relative travel path of the source and/or the detector as successive images are acquired. As shown in FIG. 3B, for linear travel of the tube head 140 using a telescoping transport apparatus in the horizontal portion 30 of the support member 135 may be advantageous for capturing successive tomosynthesis projection x-ray images of a patient at different relative angles, as shown by the dashed line ghost images of tube head 140, as between the x-ray source in tube head 140 and the detector 20.

The cutaway cross-sectional schematic view of FIG. 4 shows a portion of a conventional x-ray tube head 140 having an x-ray radiation source 50 with a collimator 22 and a collimator light 26. As referred to herein, a tube head 140 may also include filters, other light sources, a plurality of x-ray sources such as cold cathode (CC) or carbon nanotube (CNT) x-ray sources, a vacuum sealed enclosure for one or more x-ray sources, a housing to enclose tube head components, a display screen which may include a touch screen, control knobs, handles for manually maneuvering the tube head into position, and other components as described herein. Collimator 22 typically has two collimator sections 76 a and 76 b, each with blades positioned for shaping the output radiation beam. A collimator light 26, typically a light bulb or light emitting diode (LED) or other solid-state light source, mounts inside collimator 22 and serves as a guide for aiming orientation of the x-ray head 140. A mirror 24, essentially transparent to x-rays but reflective to visible light, combines the light path of collimator light 26 with the radiation path R of x-ray beam 32 that extends from the x-ray source, so that the cross-sectional area of the light beam from collimator light 26 matches the cross-sectional area of the collimated radiation beam that is emitted from x-ray head 140.

The perspective view of FIG. 5 shows the function of collimator light 26, which typically projects a lighted pattern 23 to assist registration of the patient to the source so that the collimated beam is directed to the subject region that is properly within the perimeter of the detector 20. As has been emphasized, however, it is generally not feasible to identify the exact position and skew orientation of detector 20 relative to the x-ray beam 32 from x-ray head 140 for mobile radiography applications, for reasons such as detector placement and condition of the patient.

According to embodiments of the present disclosure, geometric calibration of the source and detector is performed using the acquired radiography image content. Radio-opaque markers 40 are disposed within or external to x-ray head 140 at fixed positions along, or proximate to, a central radiation path R in the radiation beam 32. The image content that is acquired at, or captured by, the x-ray detector 20 includes the markers 40. The position of the markers in the acquired x-ray image relates directly to the relative geometry of the x-ray source 50 and detector 20 and can be used to calculate this geometry with sufficient accuracy to provide a faithful reconstruction of depth information for the imaged patient anatomy.

Referring to the simplified schematic diagram of FIG. 6, mirror 24 of x-ray head 140 is shown in relation to the position of collimator light 26 and x-ray source 50. Mirror 24 has been modified to include a set of radio-opaque markers 40, each marker 40 disposed in path R of the x-ray radiation beam 32 directed toward detector 20. Because each marker 40 is radio-opaque, the markers 40 are detected in the x-ray image content from detector 20 and so appear in the captured x-ray image visible to medical personnel so long as the marker image is not digitally removed or erased. The pattern of markers 40 that are imaged by detector 20 and the overall geometry of the detected pattern provide sufficient information for an accurate spatial calibration of detector 20 relative to a position of x-ray source 50.

It should be noted that, while mirror 24 can be a convenient vehicle for mounting of the radio-opaque markers within x-ray head 140, other components within the x-ray head 140 that lie in the radiation path R can alternately be used, such as filters, for example. The markers can be coupled to, or formed as part of, a suitable radio transparent, or radiolucent, support surface or to some other feature that is in the path of the radiation beam and collimator light. In one embodiment, a radiolucent marker substrate, or support surface, having radiopaque markers therein, may be inserted into, or otherwise attached to, the tube head.

There are a number of considerations that relate to marker use for geometric calibration of a mobile radiography apparatus, including the following:

-   -   (i) Marker positioning along the periphery of the radiation         field. Peripheral positions of markers 40 with respect to the         detector imaging area are generally advantageous. Anatomical         information of interest is generally centered in the image area;         markers 40 along the edges or outside of the imaged area are         less likely to interfere with 3D reconstruction.     -   (ii) Fixed positioning. Marker positions may be fixed inside or         outside the housing of the x-ray head 140 and their locations do         not change relative to the x-ray source or sources with         adjustment of tube head 140 position. If markers 40 are provided         on the mirror 24 as disclosed with reference to FIG. 4, the         mirror 24 should be in a fixed position within the tube head         140.     -   (iii) Calibration of markers 40 to head 140. An initial         geometric calibration of markers 40 position to the head 140 and         x-ray source 50 is performed as a setup procedure for the mobile         radiography apparatus, prior to use of markers 40 for         source/detector calibration for a patient image. This         calibration may include separation distance between markers 40         on the marker substrate, whether the substrate is the mirror 24         or a separate substrate.     -   (iv) Shadows. Markers 40 generate shadows in the acquired         projection images, i.e., marker images appear in the acquired         x-ray images. Additional image processing steps are needed in         order to remove the marker images, or shadows, following         geometric calibration. Well-known image processing procedures         such as segmentation, interpolation, and in-painting can be         employed to compensate for shadow effects.     -   (v) High magnification factor. The geometry magnification factor         for markers is significant. Thus, the markers 40 themselves         should be made as small and distinct as possible.     -   (vi) Marker shape. Specially shaped markers 40 facilitate marker         detection and removal from the projection images. For example,         circular, triangular, or cross-shaped markers 40 may be         advantaged. Although the marker shape may increase marker size,         distinctive shapes can help to simplify detection of the center         of the marker, allowing ready identification and removal.     -   (vii) Adjustable collimators. Depending on the design of x-ray         head 140, collimators 22 may be adjustable. This factor must be         taken into account for marker design and positioning. A specific         collimator position may work best for subsequent detection and         removal of marker effects.

Calibration of marker position (item (iii) above) can be performed by establishing precise positional coordinates for detector 20 relative to x-ray source 50 and acquiring image content from two or more exposures along the travel path of x-ray head 140. Calibration of marker position can then be calculated from positional and movement information from the resulting sequence of projection images, using well known methods of triangulation and projective geometry.

Using the initially calibrated marker 40 position with respect to x-ray source 50, metrics such as SID, skew, and planar orientation of the detector 20 can be readily computed using well-known projective geometry calculations.

The logic flow diagram of FIG. 7 shows a sequence for calibration of a mobile radiography apparatus having a detector that is not mechanically coupled to the x-ray source and wherein (i) the apparatus is configured with markers and (ii) marker calibration to the x-ray source has been performed. A set of 2D projection images of the subject is acquired for processing in an image acquisition step S710. Marker positions in the projection images are then identified in an identification step S720. A calculation step S730 then calculates detector/source geometry based on identified marker position, using well known projective geometry processing. A cleanup step S740 is then executed, in which marker content is removed from the projection images. Cleanup step S740 can use interpolation, in-painting, and other well known processes in order to restore image content and remove marker shadows, as noted previously. This can be readily accomplished, since the markers have the same position in each acquired projection image. A reconstruction step S750 can then be executed in order to generate the 3D volume image from corrected 2D projection images. Reconstruction methods for tomography and tomosynthesis imaging are well known and include filtered back projection (FBP) and iterative reconstruction methods, allowing a number of processing sequences to be used for volume image reconstruction. 2D slices or other portions or projections of the generated 3D volume image can then be extracted and displayed in a display step S760.

According to an embodiment of the present disclosure, only a portion of the acquired projection images in a tomosynthesis series or tomography series are analyzed for marker position detection and calculation of source/detector geometry in step S730.

Using radio-opaque markers embedded along the radiation path and executing the process outlined with respect to FIG. 7, an embodiment of the present disclosure enables source/detector geometry to be calculated from the set of projection images that is acquired. Thus, embodiments of the present disclosure are advantageous for calibration use with mobile radiography apparatus and other radiography systems in which the imaging detector is mechanically uncoupled from the radiation source.

As described herein, markers 40 can be formed of lead or other radio-opaque material, including metals such as tungsten. Markers can be formed into three dimensional volumetric beads, cubes, or into some other dimensionally suitable shape, such as a substantially flat cross or circle, a square, a triangle, or some other shape and can be adhered, imprinted by deposition onto, or embedded into, a radio-transparent, or radiolucent, surface, or otherwise coupled to a mirror, filter, or other permanent feature of, such as being attached to, the x-ray tube head 140. Markers 40 can be coupled to a radio-transparent support feature, such as onto a planar glass or plastic surface or feature, that is in the path of collimated x-ray energy from one or more x-ray sources in the tube head 140.

Turning to FIGS. 8A-8D, a tube head 140 may include multiple x-ray sources in the form of cold cathode or CNT x-ray sources 801 attached to a source support member 810 a-d. In one embodiment, six x-ray sources 801 may be arranged linearly using a linear source support member 810 a. In one embodiment, seven x-ray sources 801 may be arranged angularly using an angular source support member 810 b. In one embodiment, ten x-ray sources 801 may be arranged rectilinearly using a rectangular source support member 810 c. In one embodiment, six x-ray sources 801 may be arranged circularly using a circular source support member 810 d. X-ray source arrangements having a plurality of x-ray sources may be configured to controllably fire one or more of the x-ray sources once or in a programmed sequence, such as for acquiring a number of projection x-ray images to be used in a volume x-ray image reconstruction. In one embodiment, multiple cold cathode or CNT sources 801 supported by linear support member 801 a may be programmably fired in a timed sequence to capture a series of x-ray projection images quickly, without requiring movement of a single-source tube head along a linear path such as shown in the embodiment of FIG. 3B. FIG. 8E shows additional exemplary patterns or arrangements of x-ray sources 801 secured to source support members 810 e, 810 f, and 810 g, in a cross shape, a triangular shape, and a curvilinear shape, respectively, which are operatively attachable to, and usable with, tube head 140 similar to the embodiments of FIGS. 8A-8D. The arrangement of x-ray sources or number of x-ray sources per arrangement are not limited to the examples disclosed herein and may vary to any extent desired.

FIG. 9 is a schematic diagram of side views of exemplary radiolucent planar marker substrates 940 a, 940 b, having radiopaque markers 40 supported thereby, as described herein. The marker substrates 940 a, 940 b, may be made from glass, plastic or other suitable radiolucent material. As disclosed herein, radiopaque markers 40 may be shaped as substantially flat circular, triangular, square, cross, or other shape markers 40, deposited onto a surface of, embedded at any desired depth into a surface of, or otherwise supported by, marker substrate 940 a. Similarly, radiopaque markers 40 may be shaped as volumetric spheres, cubes, or other three dimensional shape markers 40, embedded into the radiolucent substrate or otherwise supported by marker substrate 940 b. In one embodiment, distances d between selected ones of the radiopaque markers 40 are precisely known. In one embodiment, distances d between all markers 40 supported by marker substrate 940 a, 940 b, are precisely known.

FIG. 10 is a schematic diagram of an exemplary imaging system including a tube head 1001 having a housing 1003 enclosing a plurality of CC or CNT x-ray sources 801 each configured to emit an x-ray beam 32, when activated, toward DR detector 20 to capture x-ray projection images of a portion of a patient 14. In the exemplary embodiment of FIG. 10, two radiolucent marker substrates 940 are used simultaneously, each having a plurality of radiopaque markers supported thereby (markers not shown) in the x-ray beams 32 emitted by the x-ray sources. Each of the marker substrates 940 is positioned at a different distance from the tube head 1001. The number of CC or CNT x-ray sources 801 included in tube head 1001 may include any desired number that is electromechanically feasible for tomosynthesis imaging. All, or a subset, of the x-ray sources 801 may be preselected for activation to capture tomosynthesis images of a patient 14.

FIG. 11 is a schematic diagram of a tube head housing 1003 enclosing a plurality of CC or CNT x-ray sources 801 each configured to emit an x-ray beam 32 a, 32 b, 32 c, toward DR detector 20. Tube head 1001 is shown having twelve x-ray sources 801, however, any other desired number of x-ray sources 801 may be included. Collimator section 22 of tube head 1001 selectively collimates the x-ray beams 32 a-32 c of each activated x-ray source 801. The x-ray sources 801 may each be enclosed in a different vacuum chamber, or vacuum tube, or, as shown in FIG. 11, the x-ray sources 801 may all be enclosed by, or sealed in, a single vacuum chamber 1101. The x-ray sources 801 are each configured to emit, when activated, an x-ray beam 32 a, 32 b, 32 c, that travels through one corresponding radiolucent marker substrate 940 x, 940 y, 940 z, respectively, that supports and disposes a plurality of radiopaque markers 40 within each of the corresponding x-ray beams 32 a, 32 b, 32 c, which radiopaque markers 40 are captured in projection x-ray images acquired by DR detector 20. In the exemplary embodiment of FIG. 11, the markers 40 and their corresponding marker substrates 940 x, 940 y, 940 z, are secured in positions within corresponding x-ray beams 32 a, 32 b, 32 c, outside of the tube head housing 1003. In the exemplary embodiment of FIG. 11, the x-ray sources 801 are fired one at a time in a programmed sequence, thereby emitting x-ray beams 32 a, 32 b, 32 c, one at a time, while the DR detector 20 captures one projection x-ray image for each firing of an x-ray source. In the exemplary embodiment of FIG. 11, the x-ray sources 801 are shown to be arranged linearly along linear source support member 810 a, however, a suitable tube head housing 1003 may be used to enclose any shape arrangement of x-ray sources 801 disclosed herein, such as in FIGS. 8B-8E. In the exemplary embodiment of FIG. 11, only three of the exemplary x-ray sources 801 are illustrated as activated in cooperation with corresponding radiolucent marker substrates 940 for ease of illustration. In actual operation, each of the twelve x-ray sources 801 in FIG. 11 may be configured in a similar manner as illustrated by the three exemplary activated x-ray sources 801. All, or any subset, of the twelve x-ray sources 801 may be preselected for programmed sequential firing during a tomosynthesis imaging scan, or tomosynthesis imaging examination.

FIG. 12 is a schematic diagram of a tube head housing 1003 enclosing a plurality of CC or CNT x-ray sources 801 each configured to emit an x-ray beam 32 a, 32 b, 32 c, toward DR detector 20. Tube head 1001 is shown having twelve x-ray sources 801, however, any other desired number of x-ray sources 801 may be included. Collimator section 22 of tube head 1001 selectively collimates the x-ray beams 32 a-32 c of each activated x-ray source 801. The x-ray sources 801 may each be enclosed in a different vacuum chamber, or vacuum tube, or, as shown in FIG. 12, the x-ray sources 801 may all be enclosed by, or sealed in, a single vacuum chamber 1101. The x-ray sources 801 are each configured to emit, when activated, an x-ray beam 32 a, 32 b, 32 c, that travels through one corresponding radiolucent marker substrate 940 m, 940 n, 940 o, respectively, that supports a plurality of radiopaque markers 40 therein within each of the corresponding x-ray beams 32 a, 32 b, 32 c, which markers 40 are captured in projection x-ray images acquired by DR detector 20. In the exemplary embodiment of FIG. 12, the markers 40 and their corresponding marker substrates 940 m, 940 n, 940 o, are secured in positions within corresponding x-ray beams 32 a, 32 b, 32 c, inside of the tube head housing 1003. Because the marker substrates 940 m, 940 n, 940 o, are positioned closer to the x-ray sources 801 in the embodiment of FIG. 12, the marker substrates 940 m, 940 n, 940 o, are sized smaller than the marker substrates 940 x, 940 y, 940 z, in the embodiment of FIG. 11. The marker substrates 940 m, 940 n, 940 o, may be attached to interior portions of tube head housing 1003. In the exemplary embodiment of FIG. 12, similar to the embodiment of FIG. 11, the x-ray sources 801 are fired one at a time in a programmed sequence, thereby emitting x-ray beams 32 a, 32 b, 32 c, one at a time, while the DR detector 20 captures one projection x-ray image for each firing of an x-ray source 801. In the example embodiment of FIG. 12, the x-ray sources 801 are shown to be arranged linearly along linear source support member 810 a, however, a suitable tube head housing 1003 may be used to enclose any shape arrangement of x-ray sources 801 disclosed herein. In the exemplary embodiment of FIG. 12, only three of the exemplary x-ray sources 801 are illustrated as activated in cooperation with corresponding radiolucent marker substrates 940 for ease of illustration. In actual operation, each of the twelve x-ray sources 801 in FIG. 12 may be configured in a similar manner as illustrated by the three exemplary activated x-ray sources 801. All, or any subset, of the twelve x-ray sources 801 may be preselected for programmed sequential firing during a tomosynthesis imaging scan, or tomosynthesis imaging examination.

FIG. 13 is a schematic diagram of a tube head housing 1003 enclosing a plurality of CC or CNT x-ray sources 801 each configured to emit an x-ray beam 32 a, 32 b, 32 c, toward DR detector 20. Tube head 1001 is shown having twelve x-ray sources 801, however, any other desired number of x-ray sources 801 may be included. Collimator section 22 of tube head 1001 selectively collimates the x-ray beams 32 a-32 c of each activated x-ray source 801. The x-ray sources 801 may each be enclosed in a different vacuum chamber, or vacuum tube, or, as shown in FIG. 13, the x-ray sources 801 may all be enclosed by, or sealed in, a single vacuum chamber 1101. The x-ray sources 801 are each configured to emit, when activated, an x-ray beam 32 a, 32 b, 32 c, that travels through a radiolucent marker substrate 940 that supports a plurality of radiopaque markers 40 a-40 f. At least a subset of the radiopaque markers 40 a-40 f are positioned in each of the x-ray beams 32 a, 32 b, 32 c, which markers 40 a-40 f that are in an x-ray beam 32 a, 32 b, 32 c, during imaging are captured in projection x-ray images acquired by DR detector 20. In a preferred embodiment, at least three of radiopaque markers 40 a-40 f are disposed in an activated x-ray beam 32 a, 32 b, 32 c, from any of the x-ray sources 801 during image capture, and appear in each radiographic image acquired by DR detector 20. In one exemplary embodiment, markers 40 a, 40 b, and at least one other marker may be positioned within x-ray beam path 32 a during image capture. In another exemplary embodiment, markers 40 c, 40 d, and at least one other marker may be positioned within x-ray beam path 32 b during image capture. In another exemplary embodiment, markers 40 e, 40 f, and at least one other marker may be positioned within x-ray beam path 32 c during image capture. In another exemplary embodiment, markers 40 a-40 f may all be positioned within each of exemplary x-ray beam paths 32 a-32 c to be captured in corresponding images acquired by DR detector 20. In the exemplary embodiment of FIG. 13, similar to the embodiment of FIG. 11, the x-ray sources 801 are fired one at a time in a programmed sequence, thereby emitting x-ray beams 32 a, 32 b, 32 c, one at a time, while the DR detector 20 captures one projection x-ray image for each firing of an x-ray source 801 which captured projection images each include at least three of the radiopaque markers supported by substrate 940 appearing therein.

In the exemplary embodiment of FIG. 13, the marker substrate 940 is secured in position within the x-ray beams 32 a, 32 b, 32 c, using a rigid support arm 1301 attached to a portion of tube head 1001, or support arm 1301 may be attached to another portion of mobile radiography apparatus 100, or it may be independently supported. In the example embodiment of FIG. 13, the x-ray sources 801 are shown to be arranged linearly along linear source support member 810 a, however, tube head housing 1003 may be used to enclose any shape arrangement of x-ray sources 801 disclosed herein. In the exemplary embodiment of FIG. 13, only three of the exemplary x-ray sources 801 are illustrated as activated in cooperation with corresponding radiolucent marker substrate 940 for ease of illustration. In actual operation, each of the twelve x-ray sources 801 in FIG. 13 may be activated in a similar manner as illustrated by the three exemplary activated x-ray sources 801. All, or any subset, of the x-ray sources 801 may be preselected for programmed sequential activation during a tomosynthesis imaging scan, or tomosynthesis imaging examination.

FIG. 14 is a perspective view of a mobile radiography apparatus 100 guided into position at the bedside of a patient 14 in a medical imaging facility. The horizontal section 30 of support member 135 includes tube head 1001, as described herein, attached thereto. In the embodiment of FIG. 14, x-ray sources within the tube head 1001 are configured to emit a preselected plurality of x-ray beams 32, as described herein, toward either of DR detector 20 or movable DR detector 1401 to capture tomosynthesis projection images of a portion of the patient 14, as described herein. In the exemplary embodiment of FIG. 14, movable DR detector 1401 may be positioned beneath patient 14 in a motorized bucky attached to a patient bed 1400 that enables programmed movement of the DR detector 1401 along dimension 1403 during a programmed tomosynthesis projection imaging sequence of patient 14. The DR detector 1401 may be programmed by motor control to move to different positions beneath patient 14 for each sequential firing of preselected x-ray sources 801 in the tube head 1001.

FIG. 15 illustrates the arrangement of FIG. 14 having rigid support arm 1501 attached to the horizontal section 30 of support member 135 (FIG. 14) and to the radiolucent marker substrate 940 to secure in position the radiopaque markers 40, supported by marker substrate 940, in the path of x-ray beams 32 (FIG. 14), as described herein with respect to FIG. 13. In one embodiment, support arm 1501 may be attached to radiolucent marker substrate 940 and to another portion of the mobile radiography apparatus 100, such as to the vertical section of the support member 135 (FIG. 14). In one embodiment, the radiolucent marker substrate 940 may be attached to a rigid support arm 1503 that is independently fixed in position, without attachment to any portion of the mobile radiography apparatus, such as by attachment to a floor of an x-ray imaging facility as shown in FIG. 15, or to another structural portion of an x-ray imaging facility, such as a ceiling or a wall 1504 of the imaging facility.

With reference to FIG. 16, rigid support arm 1503 may have marker substrate 940 attached thereto, as shown in FIG. 15, or a different marker support structure attached thereto. Rigid support arm 1503 may be rigidly attached to a wheeled transport frame 1601 by sliding rigid support arm 1503 into a hollow support pillar 1602. The transport frame 1601 together with rigid support arm 1503 secured thereto, and either marker substrate 940 or a different marker support structure attached to rigid support arm 1503, may be manually guided into place at a patient bedside for positioning radiopaque markers 40 in the path of x-ray beams for radiographic imaging as described herein. In one embodiment, radiopaque markers 40 may each be individually attached to radiolucent support rods 1603 which, in turn, are movably attached to a support frame 1605, which support frame 1605 is rigidly attached to the rigid support arm 1503. The support frame 1605 may also be made from a radiolucent material. Each of the radiolucent support rods 1603 may be movable horizontally and vertically, as shown by the arrows in FIG. 16, to manually space apart the radiopaque markers 40, as desired. In addition, the assembly of radiopaque markers 40, radiolucent support rods 1603, and support frame 1605, may be detached from rigid support arm 1503 in order to swap in the marker substrate 940. Thus, the assembly of radiopaque markers 40, radiolucent support rods 1603, and support frame 1605, may be attached to rigid support arm 1503 in place of marker substrate 940, and also be guided into position, at a patient bedside as shown in FIG. 15, to place the radiopaque markers 40 in the path of x-ray beams for radiographic imaging as described herein. Although three radiopaque markers 40 are shown attached to three radiolucent support rods 1603, the support frame 1605 may include more than three support rods 1603 each having a radiopaque marker 40 attached thereto.

With reference to FIGS. 17A-17B, there are illustrated exemplary methods of operating the mobile radiography apparatus 100 as described herein having the tube head 1001 as described herein. FIG. 17A illustrates an exemplary sparse sampling, under-sampling, or sub-sampling method or technique whereby a preselected subset s of five x-ray sources 801 are programmably sequentially activated, or fired, to capture a plurality of tomosynthesis projection images of a patient 14 in portable DR detector 20. FIG. 17A also illustrates an exemplary sparse sampling method whereby an angular sampling rate between projection image captures is decreased by 3× or, in other words, the imaging interval angle is increased by 3× because every third one of the x-ray sources 801 are preselected for activation during an image capture sequence. As referred to herein, the terms sparse, sub-, or under-, sampling means that about one-half to about one-tenth of the x-ray sources 801 available for a full, or standard, tomosynthesis projection scan of patient 14 are activated. The term full set or standard set of tomosynthesis projection images may be used to indicate that all of the x-ray sources, that are available for use across a full angular range, are used to capture tomosynthesis projection images. Thus, a full set, or standard set, of tomosynthesis projection images may contain about two to about ten times the number of projection images of a patient anatomy, as compared to a sparse set, to be used for a volume (3D) image reconstruction of the patient anatomy. Furthermore, the term sparse volume image, or just “sparse”, may be used to refer to a 3D volume image reconstructed from a sparse set of tomosynthesis projection images as opposed to a full volume image, or, in general, to any images produced by a sparse sampling technique described herein. Similarly, the term full volume image, or just “full”, may be used to refer to a 3D volume image reconstructed from a full set of tomosynthesis projection images, or, in general, to any images produced by a full, or standard, sampling technique described herein. As shown in the exemplary method of FIG. 17A, a subset s of five, out of thirteen available, x-ray sources 801 are used to capture tomosynthesis projection images of patient 14. In this example, the sparse sampling ratio is 5/13 and the angular range is the same as might be used in a standard tomosynthesis scan using all thirteen of the x-ray sources in the tube head 1001 of FIG. 17A. The sparse angular sampling rate may be defined as one-third of a full angular sampling rate because the angular interval is increased by 3×. As used herein, the angular sampling rate refers to a number of projection images captured per angular degree of translation as between an x-ray source relative to the x-ray detector.

FIG. 17B illustrates an exemplary sparse sampling, under-sampling, or sub-sampling technique whereby a preselected subset s of three x-ray sources 801 within a limited angular range 1701 are programmably activated, or fired, to capture a plurality of tomosynthesis projection images of a patient 14 in DR detector 20. As referred to herein, a sparse sampling with limited angular range means that about two-fifths to about four-fifths of the angular range available for a full, or standard, tomosynthesis projection scan of patient 14 is used. Thus, a full angular range, or standard angular range, of tomosynthesis projection images may contain projection images of a patient anatomy at about a 25% to about a 250% greater angular range, as compared to a sparse sampling with limited angular range, to be used for a volume (3D) image reconstruction of the patient anatomy. As shown in the exemplary method of FIG. 17B, the three exemplary preselected x-ray sources s within the angular range 1701 subtend an angle about three-fourths (75%) of the full angular range if all five x-ray sources 801 were used. In this example, the sparse sample is a three-fourths limited angular range and the number of x-ray sources used is also less than the number available in a standard tomosynthesis scan using all the x-ray sources 801 in the tube head 1001 of FIG. 17B.

FIG. 18 illustrates an exemplary method of determining an angular range or limited angular range using the tube head example of FIG. 17B. A line 1801 from an x-ray source 1800 in a central position of the x-ray sources 801 to be used for tomosynthesis projection imaging is extended perpendicular to the tube head 1001 to an intersection point with a plane of the portable DR detector 20. Lines 1803 are extended from the outermost x-ray sources of the tube head 1001 to the intersection point. These lines 1803 define the full angular range of the tube head 1001. Lines 1805 are extended from the outermost x-ray sources to be used for a current tomosynthesis projection imaging sequence, using a limited angular range, to the intersection point. These lines 1805 define the limited angular range or the sparse angular range. In the example of FIG. 17B, the sparse angular range is slightly less than 75%, or three fourths, of the full angular range.

Another sparse sampling technique that may be referred to herein includes decreasing an energy level of each activation, or firing, of an x-ray source 801, as compared to a standard or full energy level normally used for a tomosynthesis imaging sequence, during a low dose tomosynthesis projection imaging examination. This decreased energy level reduces a radiation exposure for the patient. The sparse, or low dose, energy level may be reduced by about 10% to about 50% of the full energy level normally used for tomosynthesis projection imaging. A sparse energy level may be used to acquire tomosynthesis projection images of a patient over a full angular range while acquiring a full number of tomosynthesis projection images. In one embodiment, a combination of sparse sampling techniques may be used simultaneously, such as a reduced x-ray source energy level (sparse energy) and a reduced angular range (sparse or limited angular range). In another embodiment, sparse energy may be used together with a reduced (sparse) number of tomosynthesis projection images (sparse sampling). Each of the sparse sampling techniques described herein may result in certain defects that are visible in volume reconstructions generated therefrom. These defects may include excessive noise, streaks, and ring artifacts appearing in the volume reconstructions. As described herein, an artificial intelligence network, such as a convolutional neural network, may be implemented to reduce such image defects to provide a high resolution image volume while implementing sparse sampling techniques. As described herein, sparse sampling techniques may be intentionally implemented to reduce patient radiation dose by as much as 20× (down to 5%) of the dose normally used in conventional tomosynthesis systems.

FIG. 19 illustrates an exemplary method of training an artificial intelligence system 1904, that includes an artificial intelligence network, or module, 1905, to generate a high resolution tomosynthesis volume image based on sparsely sampled projection images. In the exemplary method of FIG. 19 a convolutional neural network (CNN) commonly referred to as a U-net 1905 will be used as the exemplary artificial intelligence network to be trained. Such neural networks are well known and details of their internal operation are not described herein. To train the U-net 1905, a sparse volume reconstruction 1901 is provided as one input to the U-net 1905. This sparse volume reconstruction 1901 may include image defects as described herein. A full volume reconstruction 1902 is combined with the sparse volume reconstruction 1901 in a subtraction step 1903 to generate a difference file 1906 which records actual, or true, differences as between the full volume reconstruction 1902 and the sparse volume reconstruction 1901. This difference file 1906 is provided as a comparison input to the system 1904. The sparse set of projection images that are used to generate the sparse volume reconstruction 1901 consist of a subset of projection images selected from the full set of projection images used to reconstruct the full volume image 1902.

The U-net 1905 outputs a predicted correction 1909 for the input sparse volume reconstruction 1901 to remove image defects therefrom, which predicted correction 1909 is then compared to the actual differences 1906. This comparison generates a loss function 1907 which reflects an error value as between the predicted correction 1909 and the actual differences 1906. The loss function 1907 is fed back to the U-net 1905, which then uses the loss function to update its predicted correction 1909 for another comparison with the actual differences 1906. This sequence of prediction-compare-error-feedback iterates until a sufficiently low loss function is achieved, or until another suitable programmed termination criteria is reached, whereupon training of the neural network 1905 may be said to be completed.

FIG. 20 illustrates use of the trained neural network, or U-net, 2005. A patient may be radiographically imaged as described herein using a sparse sampling technique to acquire a sparse set of tomosynthesis projection images. The sparse set of tomosynthesis projection images are used to reconstruct a sparse image volume 2001. The sparse image volume 2001 is input to the trained U-net 2005 which, in turn, generates a highly accurate predicted correction 2003. The predicted correction 2003 is combined (e.g., added) to the sparse image volume 2001 to generate a final high resolution volume image 2007 based on a sparsely sampled set of tomosynthesis projection images.

FIG. 21 is an exemplary flow chart of a computer implemented method for processing sparsely sampled tomosynthesis projection images as generally described herein in reference to FIGS. 19-20. At step 2101, a first step of training a neural network includes acquiring a full set of tomosynthesis projection images and using the acquired images to reconstruct a full volume image. As used herein, reconstruction techniques are well known and are not described in detail. Several reconstruction are iterative, and may include filtered back projection as one example. At step 2102, a sparse volume image is reconstructed from a subset of the full set of acquired tomosynthesis projection images. The subset may be preselected, such as by selecting tomosynthesis projection images from the full set at periodic angular intervals. A size of the subset may range from about one-half (50%) to about one-tenth (10%) of the full set of tomosynthesis projection images. At step 2103, differences between the reconstructed full volume image and the reconstructed sparse volume image is determined. This may be accomplished by well known subtraction methods as between corresponding pixels, or voxels, of the two volume images. A difference map corresponding to the determined differences may be stored for later use. At step 2104, the reconstructed sparse volume image and the determined difference map are provided as inputs to a neural network for training the neural network as described herein with reference to FIG. 19. At step 2105, after the neural network is trained, tomosynthesis projection images of a current patient anatomy may be captured, such as during a patient exam, using any one or more sparse sampling techniques described herein. A sparse volume image of the current patient anatomy is reconstructed using the sparse set of captured tomosynthesis projection images. Typically, the sparse volume image contains image defects that may be corrected by the trained neural network. At step 2106, the reconstructed current sparse volume image is input to the trained neural network. The trained neural network applies an accurate predicted correction to the input sparse volume image, such as by adding a correction map, and outputs a high resolution corrected version of the reconstructed sparse volume image whereby defects in the initial sparse volume image are reduced or eliminated.

As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method, or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.), or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “service,” “circuit,” “circuitry,” “network,” “module,” and/or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code and/or executable instructions embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Python, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages such as Python. The program code may execute entirely on the user's device (mobile radiography apparatus), partly on the user's device, as a stand-alone software package, partly on the user's device and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal language of the claims. 

What is claimed is:
 1. A computer implemented radiographic image processing method, the method comprising: training a convolutional neural network to correct image defects in an image volume reconstructed from sparsely captured tomosynthesis projection images; sparsely capturing tomosynthesis projection images of a patient anatomy within an angular range between about two-thirds of a full angular range to about four-fifths of the full angular range using at least one x-ray source and a digital radiographic (DR) detector; reconstructing a sparse volume image of the patient anatomy using the sparsely captured tomosynthesis projection images of the patient anatomy and providing the reconstructed sparse volume image of the patient anatomy to the trained convolutional neural network; and the trained neural network outputting a corrected reconstructed sparse volume image of the patient anatomy.
 2. The method of claim 1, wherein the step of training comprises: reconstructing a full tomosynthesis volume image from a full set of acquired tomosynthesis projection images; reconstructing a sparse tomosynthesis volume image from a preselected subset of the full set of acquired tomosynthesis projection images determining differences between the full tomosynthesis volume and the sparse tomosynthesis volume image; and providing the reconstructed sparse tomosynthesis volume image and the determined differences to the convolutional neural network.
 3. The method of claim 2, wherein the step of sparsely capturing comprises at least one of capturing a plurality of tomosynthesis projection images over a preselected limited angular range within the angular range between about two-thirds to about four-fifths of the full angular range and capturing a preselected sparse number of tomographic projection images within the angular range between about two-thirds to about four-fifths of the full angular range.
 4. The method of claim 1, further comprising: positioning a plurality of radiopaque markers in a path of an x-ray beam used for the step of sparsely capturing; and calculating a position of the DR detector relative to the at least one x-ray source according to positions of the radiopaque markers in the sparsely captured tomosynthesis projection images.
 5. The method of claim 4, further comprising positioning a plurality of x-ray sources in a linear or curvilinear pattern for the step of sparsely capturing the tomosynthesis projection images of the patient anatomy.
 6. A mobile radiography system comprising a mobile base; a support arm attached to the mobile base; an x-ray tube head attached to one end of the support arm, the x-ray tube head comprising one or more x-ray sources; a portable DR detector mechanically uncoupled from the x-ray tube head, the portable DR detector and the x-ray tube head configured to sparsely capture tomosynthesis projection images of a patient anatomy over a preselected angular range at about every two degrees to about every five degrees over the preselected angular range; a processing system for reconstructing a sparse volume image of the patient anatomy using the sparsely captured tomosynthesis projection images; and an artificial intelligence module trained to correct the reconstructed sparse volume image and to output a corrected reconstructed sparse volume image.
 7. The system of claim 6, wherein the tube head comprises a plurality of x-ray sources arranged in a linear or curvilinear pattern.
 8. The system of claim 6, further comprising a plurality of radiopaque markers, the radiopaque markers disposed in one or more radiation paths each extending from one of the x-ray sources to the portable DR detector, and wherein the processing system is programmed to calculate a position of the portable DR detector relative to the one or more x-ray sources according to positions of the radiopaque markers appearing in the sparsely captured tomosynthesis projection images of the patient anatomy.
 9. The system of claim 8, wherein the processing system is further programmed to digitally remove the radiopaque markers appearing in the sparsely captured tomosynthesis projection images.
 10. The system of claim 6, further comprising a mobile cone beam computed tomography system.
 11. A computer implemented radiographic image processing method, the method comprising: training a convolutional neural network to correct image defects in an image volume reconstructed from sparsely captured tomosynthesis projection images; sparsely capturing tomosynthesis projection images of a patient anatomy at about one-third to about one-fourth of a standard number of tomosynthesis projection images of the patient anatomy using at least one x-ray source and a digital radiographic (DR) detector; reconstructing a sparse volume image of the patient anatomy using the sparsely captured tomosynthesis projection images of the patient anatomy and providing the reconstructed sparse volume image of the patient anatomy to the trained convolutional neural network; and the trained neural network outputting a corrected reconstructed sparse volume image of the patient anatomy.
 12. The method of claim 11, wherein the step of training comprises: reconstructing a full tomosynthesis volume image from a full set of acquired tomosynthesis projection images; reconstructing a sparse tomosynthesis volume image from a preselected subset of the full set of acquired tomosynthesis projection images determining differences between the full tomosynthesis volume image and the sparse tomosynthesis volume image; and providing the reconstructed sparse tomosynthesis volume image and the determined differences to the convolutional neural network.
 13. The method of claim 11, wherein the step of sparsely capturing comprises at least one of capturing a plurality of tomosynthesis projection images over a preselected limited angular range and capturing a preselected sparse number of tomographic projection images over a full angular range.
 14. The method of claim 11, further comprising sparsely, capturing tomosynthesis projection images of the patient anatomy within an angular range between about two-thirds of a full angular range to about four-fifths of the full angular range.
 15. The method of claim 11, further comprising sparsely capturing tomosynthesis projection images of the patient anatomy at about every two degrees to about every five degrees over a preselected angular range.
 16. The method of claim 11, further comprising: positioning a plurality of radiopaque markers in a path of an x-ray beam used for the step of sparsely capturing; and calculating a position of the DR detector relative to the at least one x-ray source according to positions of the radiopaque markers in the sparsely captured tomosynthesis projection images.
 17. The method of claim 16, further comprising positioning a plurality of x-ray sources in a linear or curvilinear pattern for the step of sparsely capturing the tomosynthesis projection images of the patient anatomy. 